Real-world study shows the potential of gait authentication to enhance smartphone security

Date:
December 10, 2021
Source:
University of Plymouth
Summary:
A study showed that -- within an appropriate framework -- gait
recognition could be a viable technique for protecting individuals
and their data from potential crime.



FULL STORY ========================================================================== Real-world tests have shown that gait authentication could be a viable
means of protecting smartphones and other mobiles devices from cyber
crime, according to new research.


==========================================================================
A study led by the University of Plymouth asked smartphone users to go
about their daily activities while motion sensors within their mobile
devices captured data about their stride patterns.

The results showed the system was on average around 85% accurate in
recognising an individual's gait, with that figure rising to almost 90%
when they were walking normally and fast walking.

There are currently more than 6.3billion smartphone users around the
world, using their devices to provide a wide range of services and to
store sensitive and confidential information.

While authentication mechanisms -- such as passwords, PINs and biometrics
- - exist, studies have shown the level of security and usability of
such approaches varies considerably.

Writing in Computers & Security, the researchers say the study illustrates
that -- within an appropriate framework -- gait recognition could
be a viable technique for protecting individuals and their data from
potential crime.



========================================================================== Academics from Plymouth's Centre for Cyber Security, Communications and
Network Research have been focused upon developing a range of innovative authentication mechanisms to provide more secure and usable solutions.

This study builds upon that prior work through the evaluation of a multi- algorithmic gait recognition system and are the first to apply this
using real- world data.

For the research, 44 participants aged between 18 and 56 were each asked
to carry a globally available smartphone device for seven to 10 days.

They were asked to place the smartphone in a belt pouch to record the
sensor data captured by the device's gyroscope and accelerometer during
the course of different physical activities.

Each participant generated an average of 4,000 sample activities during
the course of the test, with these split into records showing normal
and fast walking in addition to climbing and descending stairs.

This showed a potential error rate of 11.38% and 11.32% for normal and
fast walking respectively, with the figure rising to 24.52% and 27.33%
when participants were going down and upstairs respectively.

The researchers say this emphasises the need to further advance the
ability to automatically differentiate a wider set of walking activities
so that a multi- algorithmic approach to identification can target
specific walking characteristics.

Nathan Clarke, Professor of Cyber Security and Digital Forensics at
the University of Plymouth and recently made a Fellow of the Chartered Institute of Information Security, said: "As smartphones have developed, security controls have had to advance significantly. This has led to
a significant rise in user authentication, where users repeatedly
need to authenticate both their devices and the numerous apps they
contain. Gait authentication has emerged as a non- intrusive way of
capturing a necessary level of personal information, but - - until now --
all tests of it have taken place in a controlled environment.

"Gait recognition alone will not be the answer to usable and convenient authentication, however it could form a critically important tool
within the cyber arsenal that could contribute towards creating a
stronger awareness of a user's identity. This study demonstrates,
for the first time outside of laboratory-controlled conditions,
what level of performance can be achieved realistically. It is clear performance levels are impacted; however the study has also shown that
for most users these issues can be overcome to an acceptable level." ========================================================================== Story Source: Materials provided by University_of_Plymouth. Original
written by Alan Williams. Note: Content may be edited for style and
length.


========================================================================== Journal Reference:
1. Hind Alobaidi, Nathan Clarke, Fudong Li, Abdulrahman
Alruban. Real-world
smartphone-based gait recognition. Computers & Security, 2022;
113: 102557 DOI: 10.1016/j.cose.2021.102557 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2021/12/211210093023.htm

--- up 6 days, 7 hours, 13 minutes
* Origin: -=> Castle Rock BBS <=- Now Husky HPT Powered! (1:317/3)